First, understanding of the distributionand conservation importance of speciesother than vertebrates is generally poor,both in forests and other ecosystems. Thisis especially the case for tropical forests,where high tree diversity introduces hugecomplexity. Similarly, little is known aboutpatterns of richness and diversity of inver-tebrate species or how their responses toenvironmental change relate to those ofvertebrates (10).A second challenge is to identify ecosys-tem types that are distinct and potentiallyin need of conservation or other manage-ment action. The Aichi Biodiversity Targetsemphasize the importance of ensuring thatall ecosystems are represented in protectedareas and highlight “unique ecosystems”as a focus for conservation action. TheInternational Union for Conservation ofNature’s Commission for Ecosystem Man-agement has begun to create a red list ofecosystems analogous to the red lists ofthreatened species (11). However, identify-ing appropriately resolved ecosystem typesand distributions has proved problematic.

Disturbance and regeneration processes
and their implications for biodiversity conservation and ecosystem service provision
are also poorly understood. Much clearer
understanding of how different measures
of diversity are linked to climate resilience
is also needed. For tropical forests, this understanding is largely lacking.

Last, for many parts of the world,
achievement of forest-related objectives, especially in relation to climate change mitigation, will depend on effective restoration.
Although knowledge is improving on how
biodiversity, ecosystem function, and ecosystem services recover in the course of restoration, it remains incomplete (12). New
approaches are emerging for incorporating
this information in land-use planning and
prioritization (13).

Remote sensing of functional traits and
assemblages of traits, as described by Asner et al., can almost certainly help with
the first two challenges by providing detailed views of tree diversity and ecosystem
types in tropical forests. The authors used
airborne hyperspectral sensors to gather
high-resolution data on seven functional
traits of rainforest canopy leaves in the Am-azon-Andes region of Peru. They then used
geostatistical modeling and a clustering
algorithm to represent functional diversity
on the basis of these traits and to map forest functional classes.

The results help to elucidate the inherent functional variation in a highly complex ecosystem that is notoriously difficult
to sample from the ground and where
many species are poorly known or new
to science. The authors point out that the
trait-based approach may link more closely
to ecosystem function than results from
traditional forest inventories. Further investigation of the links between canopy
traits and diversity in groups other than
trees could generate further conservation-relevant perspectives.

Functional trait and diversity data may
also be valuable as inputs to, and for evaluation of, ecological models of vegetation
patterns and dynamics under current and
future climates (14). They may thus help
to address questions of ecosystem function
and resilience over the longer term.

A high priority should be to expand re-mote-sensing work on functional traits anddiversity to areas of known land-use history.

A segment of the Amazon forest is shown both in natural color (top) and using laser-guided imaging
spectroscopy (LGIS) (bottom). The LGIS image shows how different the trees are in terms of the seven canopy
foliar traits detected, as described by Asner et al.